The AWS DevOps Professional Is a Beast
As I took on this feat, I quickly recognized that achieving this goal would require a more strategic approach than earning my Power BI Data Analyst or AWS Solutions Architect certifications. I recommend acquiring your AWS Solutions Architect certification at a minimum before attempting this certification, as the SA certification provides a proper understanding of the AWS ecosystem.
Furthermore, the breadth of knowledge meant to be retained is vast, and the topics themselves are multifaceted. Take Domain 1: SDLC Automation (22% of the score—the bulk of the exam). It delves into Continuous Integration and Continuous Delivery (CI/CD), a double-edged sword of sorts, as one must understand the sequential actions involved in orchestrating AWS CodePipeline stages: building, testing, deploying, and load testing.
You must first learn the AWS services and their counterparts to begin building your AWS artifacts. Additionally, you must understand deployment strategies such as in-place, blue/green, and canary. That was a lot to take in, wasn't it? Well, that's just the beginning—and only the first domain. Before you know it, you're writing reproducible deployments via YAML—this is Infrastructure as Code (IaC). A key concept that every DevOps engineer must hone, as this makes the difference in the speed, accuracy, and reusability of application deployments.
Quick Context: Who I Am
Hi, I'm Jha'Mel Thorne and I'm welcoming you along my journey of landing my first full-time cloud or DevOps role.
In January 2025, I earned my AWS Solutions Architect Associate certification. But after passing, I wasn't exactly sure of my cloud destiny. I was certified but had limited experience building end-to-end solutions beyond tutorials and hands-on labs.
From March to June, I dedicated myself to filling that gap: Infrastructure as Code, CI/CD pipelines, containers, Kubernetes, Linux, and Python. Every week and a half felt like a new course in my self-paced "Data Analyst to Cloud Engineer" curriculum. By the end of June, I'd built AWS-native pipelines, 3-tier Terraform architectures, and Python-based Docker deployments.
What came next? After conversations with a few Solutions Architects and Cloud Engineers, the consensus was clear: bridge my cloud skills with the SDLC, networking, configuration management, and distributed systems. That meant pursuing the DevOps Professional certification.
Starting in July and earning my certification on October 12th, let me walk you through my exact guide to passing this exam in under 3 months.
The Strategy: Two Sessions, One Goal
Throughout my entire cloud journey, I've had to manage my 9-5 as a data analyst at a private markets firm. Some days are demanding and mentally intensive. Outside of that, include family, my relationship, and running 10Ks and half-marathons. Time is limited.
I started the course in mid-July, but I worked through the sections half-heartedly and built mini-projects until September. Work, travel, life. My DevOps cert journey started slowly. There were entire weeks I simply didn't study at all.
The course consisted of 17 hours of content. I purchased additional Tutorial Dojo practice exams and strategically allotted time to dissect course content into digestible bites, ensuring that I could articulate concepts in interviews. Each day, I'd sign into my Udemy account and start Stéphane Maarek's course at 6:30 AM, studying until 8:00 or 8:30 AM. The goal was to break my study routine into two distinct sessions.
Working Sessions
Session 1 (morning): Actual course content. I treated it like a lecture hall. Listening, taking notes, pausing where necessary, ingesting content from a passive standpoint.
Session 2 (evening): Aggressive mode. I'd operate as a true architect: drawing diagrams, connecting learnings to real-world examples, refining my expertise in the AWS console with hands-on practice from the morning session, and operating as if I'd be directly applying the day's learnings in an interview or my day-to-day role as a DevOps engineer.
In total, I'd spend about 3 to 4 hours daily for two straight weeks finishing the course. The course is 17 hours, but 1 hour of course content cannot be processed and retained in just 1 hour. It takes reflection. It takes switching tabs to dive deep into migrations, disaster recovery, CloudFormation templates vs. Terraform, or AWS Control Tower for governance and compliant multi-account environments.
Why SDLC Clicked for Me
Here's the thing. I didn't realize it at the time, but I was already living the SDLC as a data analyst. Every Power BI report I built followed the same pattern: gather requirements, design the data model, build the visuals, test with stakeholders, deploy to the workspace, and maintain it when the source data changed. That's the SDLC. The DevOps exam just formalized what I was already doing and added automation at every stage.
The Wake-Up Call: When Two Practice Exams Humbled Me
There's a science to AWS exams. I can't say I've mastered it completely, but I've found my edge. And it came from failure.
Quick backstory: I took my Solutions Architect Associate exam twice. First attempt: 60%. I took a month off, adjusted my approach, and passed on the second try. That adjustment is what carried me through the DevOps Professional exam on the first attempt. But not before two practice exams knocked me down.
The scores that shook me:
• Configuration Management and IaC: 45%
• Monitoring and Logging: 40%
I was shocked. These were the two domains in which I felt most confident. I'd done the hands-on labs. I'd aced the mini-quizzes. I could spin up CloudFormation stacks and configure CloudWatch alarms in my sleep. So what went wrong?
I wasn't playing by the rules of AWS exams.
The Shift That Saved Me
The DevOps Professional exam is 75 questions in 180 minutes. That's 2.4 minutes per question, technically. But here's the reality: questions get longer and more complex as you go deeper into the exam. By question 50, you're reading paragraph-length scenarios with four nearly identical answer choices. If you're spending 3 minutes per question early on, you're borrowing time you won't have later.
After those failed practice exams, I changed my approach:
1. First instinct, then validate
I stopped second-guessing myself. The first answer that stood out to me was usually correct, or close enough. I'd flag it, move on, and come back during review if I had time. Spending 4 minutes convincing myself to change an answer rarely improved my score.
2. Time awareness over time management
I stopped watching the clock obsessively. Instead, I built a rhythm: read the scenario, identify the actual question (it's usually in the last sentence), eliminate the obvious wrong answer, pick from the remaining three. If two answers looked identical, I'd find the one-word difference. That's where the right answer hides.
3. Simulate exam fatigue
I started taking full 75-question practice exams in one sitting, no breaks. By question 60, my brain wanted to quit. That's exactly what the real exam feels like. Training for that fatigue was as important as learning the content.
When I retook those domain-specific exams after adjusting my approach, my scores jumped to the 70s. Not perfect, but passing. And on exam day, that rhythm carried me to an 801.
The Real Cost: Under $200
Let's talk money. One thing I rarely see in certification guides is an honest cost breakdown. Here's exactly what I spent:
That exam fee deserves context. The actual cost is $300, but here's a tip most guides skip: once you pass any AWS certification, you receive a 50% discount voucher for your next exam. I used the voucher from my Solutions Architect Associate to cut my DevOps Professional fee in half. If you're planning multiple AWS certs, stack them strategically. Each pass funds the next one at half price.
What I didn't pay for:
I didn't buy AWS Skill Builder or any additional courses. Maarek's course plus Bonso's practice exams were enough. Your mileage may vary, but I'd rather put that money toward actual AWS spend for hands-on projects.
The hidden cost:
Time. Three months of 6:30 AM wake-ups, evenings spent in the console instead of on the couch, weekends where I chose practice exams over brunch. That's not a line item, but it's real.
What I'd Do Differently
Build buffer into your timeline
Two weeks before my DevOps Professional exam, I received an unexpected opportunity: an invitation to participate in a live interview prep workshop with real hiring managers. Round-table format, small group, 30 minutes of behavioral and technical questions with immediate feedback.
This was an incredible opportunity. It also completely rerouted my study plans.
Suddenly, I wasn't drilling infrastructure drift detection or memorizing deployment configurations. I was sharpening my STAR stories, refining my career narrative, and practicing how to articulate architectural decisions under pressure. Important skills, but not what the certification exam tests.
I passed anyway. However, those final two weeks could have been dedicated to review time, and instead they were split focus. If I'd scheduled my exam with a 4-week buffer instead of 2, I could have had both: the interview prep and a final exam push.
The lesson:
Life throws unexpected opportunities at you. Some of them are worth the disruption. But if your timeline has no slack, every surprise becomes a crisis. Build the buffer. You'll either use it for the unexpected, or you'll have extra review time. Either way, you win.
Balance theory with practice, but don't skip either
Initially, I underestimated the repetition needed. Watching a lecture once wasn't enough. I'd rewatch sections two and even three times before the concepts stuck. But the real retention came when I paired theory with practice. I'd watch Maarek explain CodePipeline stages in the morning, then build an actual pipeline that evening. The lecture gave me the "what" and "why." The hands-on gave me the "how it actually behaves." Neither alone was sufficient.
The Unexpected Edge: How Power BI Prepared Me for CloudWatch
Here's something I didn't expect: my years building Power BI dashboards gave me a head start on one of the exam's core domains, Monitoring and Logging.
Think about it. In Power BI, you're constantly asking:
• What metrics actually matter to stakeholders?
• How do I visualize trends over time?
• What thresholds trigger concern?
• How do I drill down from summary to root cause?
CloudWatch is the same mental model, different tooling.
When the exam asked about setting up alarms, configuring dashboards, or choosing which metrics to monitor, I wasn't starting from zero. I was translating.
The insight that clicked:
In Power BI, I learned that a dashboard nobody looks at is a waste of effort. The same principle applies to CloudWatch. The exam tests whether you understand what to monitor, not just how to configure it. My instinct for "what does the stakeholder actually need to see?" carried over directly.
If you're coming from a data background, lean into this. You already think in metrics, thresholds, and visualizations. CloudWatch is just a new dialect of a language you already speak.
Key Takeaways:
Get your Solutions Architect first
The DevOps Professional assumes you already understand VPCs, IAM, S3, EC2, and the core AWS ecosystem. Without that foundation, you'll spend half your study time filling gaps instead of learning DevOps concepts.Two sessions beat one long session
Morning for passive learning (lectures, notes). Evening for active application (console, diagrams, practice). This isn't just time management. It's how retention actually works.Failed practice exams are data, not defeat
My 40% and 45% scores hurt. But they revealed exactly where my approach was broken. Without those failures, I wouldn't have discovered the rhythm that got me to 801.Train for fatigue, not just knowledge
75 questions in 3 hours is a mental marathon. Take full-length practice exams under real conditions. Your brain needs to know what question 60 feels like before exam day.Your background is an asset, not a gap
Coming from data analytics, I thought in terms of metrics, dashboards, and stakeholder needs. That translated directly to CloudWatch and observability concepts. Find what transfers from your experience. It's there.
What's Next
This is the first post in my "Data Analyst to Cloud Engineer" series. I'm documenting this transition in real-time: the wins, the failures, the interview stories, and the technical deep dives.
Coming up:
• EKS on Fargate: The $200 Weekend Mistake That Taught Me Cost Optimization
• IAM Roles vs. Users vs. Service Accounts: Explained for Data Analysts
• 5 AWS Interview Questions That Stumped Me (And How I'd Answer Today)
If you're on a similar journey, or thinking about starting one, follow along. And if you've already made this transition, I'd love to hear what surprised you most. Drop a comment below.
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